overview

The Multimodal Vision Research Lab conducts fundamental and applied research that is grounded in computer vision. We simultaneously focus on publishing in top-ranked computer vision venues (e.g., CVPR, ICCV, and ECCV) and working closely with domain experts to solve problems in a broad range of disciplines, including medical imaging, transportation engineering, and astrophysics. We have a supportive culture where people can do impactful research, learn new skills, and achieve their personal goals.

While most of our members have computer science (CS) backgrounds and/or are working on CS degrees, we encourage people with strong computational and quantitative skills from other disciplines to apply, including, but not limited to, Electrical Engineering, Physics, Mathematics, Statistics, and Data Science. Lab members primarily focus on implementing computer vision algorithms using Python and Pytorch. In addition, most of our projects involve some aspects of machine learning, image/signal processing, linear/nonlinear optimization, and large-scale data processing.

current openings (updated Mar 10, 2021)

We have several active openings for graduate and postdoctoral researchers (starting in Summer and Fall 2021). Topics include:

• image geo-localization of ground-level imagery
• object tracking in video
• change detection in satellite imagery

In all cases, the focus will be on developing image-understanding systems using deep-learning techniques. These projects are collaborative with industrial partners and require US citizenship or permanent resident status.

General information and expectations for each type of position:

• Postdoctoral scholars will work closely with the lab director to develop a research program that is aligned with the funding source and their personal interests and abilities. In addition to working on research problems, they will supervise graduate/undergraduate researchers, help with proposal development, and take a leading role in project management. They must have a PhD and have prior experience in publishing original research, ideally in top-tier computer science venues. Please see the Office of Postdoctoral Affairs for additional information about benefits offered to postdocs by the University of Kentucky.
• Graduate students initially focus on implementing state-of-the-art image understanding systems, and then developing an original research program. We offer both fully funded research assistantships (stipend + health + tuition) and hourly positions. We also occasionaly support unfunded research as part of an independent research class (CS 612).
• Undergraduate researchers will focus on implementing state-of-the-art image understanding systems in close collaboration with a graduate student or a postdoc. We primarily offer paid positions, but occasionaly offer unfunded research positions as part of an independent research class (CS 395). We are especially interested in students that are likely to stay for a master's degree.

qualifications

We look holistically at each applicant to determine if they are a good fit for our current and future needs. We generally look for new members with the following qualifications:

• [required] strong programming skills (we implement primarily in Python, but knowledge of Python is not required)
• [required] strong grades in math and statistics courses (minimum GPA: 3.5 for undergraduate researchers)
• [required] strong English oral and written communications skills
• [ideal] ability to build basic systems using machine learning and/or mathematical optimization
• [helpful] experience with deep learning and/or computer vision
• [helpful] ability to build large-scale data processing systems using Linux tools
• [helpful] prior research experience

applying

The following documents should be sent to the lab director, Dr. Nathan Jacobs:

• resume/CV
• a brief research statement (what are you interested in working on and why is it important?)
• transcript(s)
• one or more recommendation letter(s), which should be sent directly by the writer

In addition, be sure to include the type of position you are interested in (postdoc, graduate, or undergraduate), your funding situation, when you are available to start, and anything else you think might be helpful.